Why OLAP?

Relational databases store the world's data

Relational databases have dominated database technology by providing the online transactional processing (OLTP) that is essential for businesses to keep track of their affairs. Designed for efficient selection, storage, and retrieval of data, relational databases are ideal for housing gigabytes of detailed data.

The success of relational databases is apparent in their use to store information about an increasingly wide scope of activities. As a result, they contain a wealth of data that can yield critical information about a business. This information can provide a competitive edge in an increasingly competitive marketplace.

Analytical processing answers business questions

The challenge is in deriving answers to business questions from the available data, so that decision makers at all levels can respond quickly to changes in the business climate. While a standard transactional query might ask, "When did order 84305 ship?" an analytical query might ask, "How do sales in the Southwestern region for this month compare with plan? or with sales a year ago?"

The first question involves simple data selection and retrieval. However, the second question involves inter-row calculations, time series analysis, and access to aggregated historical and current data. This is online analytical processing -- OLAP.

The data processing required to answer analytical questions is fundamentally different from the data processing required to answer transactional questions. The following table highlights the major differences.

Characteristic	Transactional Query	Analytical Query
Typical operation	Update	Analyze
Age of data	Current	Historical
Level of data	Detail	Aggregate
Data required per query	Minimal	Extensive
Querying pattern	Individual queries	Iterative queries

Types of analytical reporting applications

Applications that support business analyses fall into these major groups:

• Standard and ad-hoc reporting

• Analytical reporting

• Predictive analysis

Oracle^® provides the technology for all of these types of applications. OLAP Services and its development tools are particularly suited to analytical reporting and predictive analysis applications.

Analytic applications can support many facets of a business and offer high returns on the investment. Here are just a few examples of analytical applications, as reported by IDC:

• Accounting. Forecasting, budgeting, cost and profitability analysis, and consolidation

• Human Resources. Skills consolidation, labor scheduling and optimization

• Distribution. Scheduling and optimization

• Sales Force Automation. Cross-selling and territory analysis

• Marketing. Churn and market-based analyses

• Retailing. Site location and demographic analysis

• Manufacturing. Demand planning and forecasting

• Health Care. Outcomes analysis

• Financial Services. Risk assessment and management

Moreover, the forecasting and modeling features enable you to develop demand planning applications.

This guide will introduce you to the tools for developing these types of applications.